erf.js (5243B)
1 /* eslint-disable no-loss-of-precision */ 2 import { deepMap } from '../../utils/collection.js'; 3 import { sign } from '../../utils/number.js'; 4 import { factory } from '../../utils/factory.js'; 5 var name = 'erf'; 6 var dependencies = ['typed']; 7 export var createErf = /* #__PURE__ */factory(name, dependencies, _ref => { 8 var { 9 typed 10 } = _ref; 11 12 /** 13 * Compute the erf function of a value using a rational Chebyshev 14 * approximations for different intervals of x. 15 * 16 * This is a translation of W. J. Cody's Fortran implementation from 1987 17 * ( https://www.netlib.org/specfun/erf ). See the AMS publication 18 * "Rational Chebyshev Approximations for the Error Function" by W. J. Cody 19 * for an explanation of this process. 20 * 21 * For matrices, the function is evaluated element wise. 22 * 23 * Syntax: 24 * 25 * math.erf(x) 26 * 27 * Examples: 28 * 29 * math.erf(0.2) // returns 0.22270258921047847 30 * math.erf(-0.5) // returns -0.5204998778130465 31 * math.erf(4) // returns 0.9999999845827421 32 * 33 * @param {number | Array | Matrix} x A real number 34 * @return {number | Array | Matrix} The erf of `x` 35 */ 36 return typed('name', { 37 number: function number(x) { 38 var y = Math.abs(x); 39 40 if (y >= MAX_NUM) { 41 return sign(x); 42 } 43 44 if (y <= THRESH) { 45 return sign(x) * erf1(y); 46 } 47 48 if (y <= 4.0) { 49 return sign(x) * (1 - erfc2(y)); 50 } 51 52 return sign(x) * (1 - erfc3(y)); 53 }, 54 'Array | Matrix': function ArrayMatrix(n) { 55 return deepMap(n, this); 56 } // TODO: For complex numbers, use the approximation for the Faddeeva function 57 // from "More Efficient Computation of the Complex Error Function" (AMS) 58 59 }); 60 /** 61 * Approximates the error function erf() for x <= 0.46875 using this function: 62 * n 63 * erf(x) = x * sum (p_j * x^(2j)) / (q_j * x^(2j)) 64 * j=0 65 */ 66 67 function erf1(y) { 68 var ysq = y * y; 69 var xnum = P[0][4] * ysq; 70 var xden = ysq; 71 var i; 72 73 for (i = 0; i < 3; i += 1) { 74 xnum = (xnum + P[0][i]) * ysq; 75 xden = (xden + Q[0][i]) * ysq; 76 } 77 78 return y * (xnum + P[0][3]) / (xden + Q[0][3]); 79 } 80 /** 81 * Approximates the complement of the error function erfc() for 82 * 0.46875 <= x <= 4.0 using this function: 83 * n 84 * erfc(x) = e^(-x^2) * sum (p_j * x^j) / (q_j * x^j) 85 * j=0 86 */ 87 88 89 function erfc2(y) { 90 var xnum = P[1][8] * y; 91 var xden = y; 92 var i; 93 94 for (i = 0; i < 7; i += 1) { 95 xnum = (xnum + P[1][i]) * y; 96 xden = (xden + Q[1][i]) * y; 97 } 98 99 var result = (xnum + P[1][7]) / (xden + Q[1][7]); 100 var ysq = parseInt(y * 16) / 16; 101 var del = (y - ysq) * (y + ysq); 102 return Math.exp(-ysq * ysq) * Math.exp(-del) * result; 103 } 104 /** 105 * Approximates the complement of the error function erfc() for x > 4.0 using 106 * this function: 107 * 108 * erfc(x) = (e^(-x^2) / x) * [ 1/sqrt(pi) + 109 * n 110 * 1/(x^2) * sum (p_j * x^(-2j)) / (q_j * x^(-2j)) ] 111 * j=0 112 */ 113 114 115 function erfc3(y) { 116 var ysq = 1 / (y * y); 117 var xnum = P[2][5] * ysq; 118 var xden = ysq; 119 var i; 120 121 for (i = 0; i < 4; i += 1) { 122 xnum = (xnum + P[2][i]) * ysq; 123 xden = (xden + Q[2][i]) * ysq; 124 } 125 126 var result = ysq * (xnum + P[2][4]) / (xden + Q[2][4]); 127 result = (SQRPI - result) / y; 128 ysq = parseInt(y * 16) / 16; 129 var del = (y - ysq) * (y + ysq); 130 return Math.exp(-ysq * ysq) * Math.exp(-del) * result; 131 } 132 }); 133 /** 134 * Upper bound for the first approximation interval, 0 <= x <= THRESH 135 * @constant 136 */ 137 138 var THRESH = 0.46875; 139 /** 140 * Constant used by W. J. Cody's Fortran77 implementation to denote sqrt(pi) 141 * @constant 142 */ 143 144 var SQRPI = 5.6418958354775628695e-1; 145 /** 146 * Coefficients for each term of the numerator sum (p_j) for each approximation 147 * interval (see W. J. Cody's paper for more details) 148 * @constant 149 */ 150 151 var P = [[3.16112374387056560e00, 1.13864154151050156e02, 3.77485237685302021e02, 3.20937758913846947e03, 1.85777706184603153e-1], [5.64188496988670089e-1, 8.88314979438837594e00, 6.61191906371416295e01, 2.98635138197400131e02, 8.81952221241769090e02, 1.71204761263407058e03, 2.05107837782607147e03, 1.23033935479799725e03, 2.15311535474403846e-8], [3.05326634961232344e-1, 3.60344899949804439e-1, 1.25781726111229246e-1, 1.60837851487422766e-2, 6.58749161529837803e-4, 1.63153871373020978e-2]]; 152 /** 153 * Coefficients for each term of the denominator sum (q_j) for each approximation 154 * interval (see W. J. Cody's paper for more details) 155 * @constant 156 */ 157 158 var Q = [[2.36012909523441209e01, 2.44024637934444173e02, 1.28261652607737228e03, 2.84423683343917062e03], [1.57449261107098347e01, 1.17693950891312499e02, 5.37181101862009858e02, 1.62138957456669019e03, 3.29079923573345963e03, 4.36261909014324716e03, 3.43936767414372164e03, 1.23033935480374942e03], [2.56852019228982242e00, 1.87295284992346047e00, 5.27905102951428412e-1, 6.05183413124413191e-2, 2.33520497626869185e-3]]; 159 /** 160 * Maximum/minimum safe numbers to input to erf() (in ES6+, this number is 161 * Number.[MAX|MIN]_SAFE_INTEGER). erf() for all numbers beyond this limit will 162 * return 1 163 */ 164 165 var MAX_NUM = Math.pow(2, 53);